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Hiring ML Engineer (Remote, India)

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Remote · India Full-time Mid Level Today

About the role

Role

We're looking for an ML Engineer to build and own the intelligence layer. You'll work across food recognition, recommendation systems, and conversational AI to create a product that genuinely improves user's health outcomes.

What You'll Build

  • Food recognition pipeline using computer Vision models API and custom models fine-tuned on firms datasets
  • Recommendation engine combining collaborative filtering and content-based filtering (nutrients, ingredients, textures)
  • Pattern detection using time-series models (LSTM/Prophet) to identify nutritional deficiencies and preference shifts early
  • RAG-based chat system grounded in verified pediatric nutrition guidelines using llms
  • Voice transcription pipeline using OpenAI Whisper, aws transcribe and likes for hands-free logging

Requirements

  • 3+ years building and shipping ML models in production
  • Strong Python skills — TensorFlow, PyTorch, scikit-learn
  • Experience with recommendation systems or time-series modeling
  • Familiarity with LLMs and RAG architectures
  • Comfortable working with APIs (Google Vision, OpenAI, USDA FoodData Central)

Nice to Have

  • Experience in health, nutrition, or pediatric applications
  • Experience fine-tuning vision models on domain-specific datasets

What We Offer

  • Early-stage equity — meaningful ownership in a growing consumer AI company
  • Remote-first, async-friendly culture
  • Direct impact on product — you own the ML roadmap
  • Competitive salary based on experience

Requirements

  • 3+ years building and shipping ML models in production
  • Strong Python skills — TensorFlow, PyTorch, scikit-learn
  • Experience with recommendation systems or time-series modeling
  • Familiarity with LLMs and RAG architectures
  • Comfortable working with APIs (Google Vision, OpenAI, USDA FoodData Central)

Responsibilities

  • Build and own the intelligence layer.
  • Work across food recognition, recommendation systems, and conversational AI to create a product that genuinely improves user's health outcomes.
  • Build food recognition pipeline using computer Vision models API and custom models fine-tuned on firms datasets
  • Build recommendation engine combining collaborative filtering and content-based filtering (nutrients, ingredients, textures)
  • Build pattern detection using time-series models (LSTM/Prophet) to identify nutritional deficiencies and preference shifts early
  • Build RAG-based chat system grounded in verified pediatric nutrition guidelines using llms
  • Build voice transcription pipeline using OpenAI Whisper, aws transcribe and likes for hands-free logging

Benefits

equity

Skills

AWS TranscribeContent-based filteringCollaborative filteringGoogle VisionLLMLSTMOpenAI WhisperProphetPythonPyTorchRAGscikit-learnTensorFlowTime-series modelingUSDA FoodData CentralVision models

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